• Title/Summary/Keyword: Analysis and Prediction System

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Life Analysis of Relays based on Life Prediction Method (수명예측 방법에 따른 계전기의 수명분석)

  • Shin, Kun-Young;Lee, Duk-Gyu;Lee, Hi Sung
    • Journal of the Korean Society of Safety
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    • v.27 no.4
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    • pp.115-120
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    • 2012
  • In order to establish preventive maintenance standards through analysis & reliability prediction of about 60,000pcs of 20kindsof relays and contractors used for Seoul subway trains, several life prediction methodologies were applied. Firstly, Occurrence, Severity, Detection were defined and predicted by applying operation characteristic of EMU to the number of actions of relays & contactors which the manufacturers generally offer as the life cycle data. Secondly, failure distribution and average life of parts were analyzed through interpretation of field data based on a lot of experience which had built up in the field for a long time. Finally, using the 217PLUS standard as a reliability prediction program, comparative analysis of use reliability and inherent reliability was done through reliability prediction at the part level and system level.

A Prediction on the Pollution Level of Outdoor Insulator with Regression Analysis (회귀분석을 활용한 옥외 절연물의 오손도 예측)

  • 최남호;구경완;한상옥
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.52 no.3
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    • pp.137-143
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    • 2003
  • The degree of contamination on outdoor insulator is ons of the most importance factor to determine the pollution level of outdoor insulation, and the sea salt is known as the most dangerous pollutant. As shown through the preceding study, the generation of salt pollutant and the pollution degree of outdoor insulator have a close relation with meteorological conditions, such as wind velocity, wind direction, precipitation and so fourth. So, in this paper, we made an investigation on the prediction method, a statistical estimation technique for equivalent salt deposit density of outdoor insulator with multiple linear regression analysis. From the results of the analysis, we proved the superiority of the prediction method in which the variables had a very close(about 0.9) correlation coefficient. And the results could be applied to establish the Pollution Prediction System for power utilities, and the system could provide an invaluable information for the design and maintenance of outdoor insulation system.

A Study on the Reliability and Maintainability Analysis Process for Aircraft Hydraulic System (항공기용 유압 시스템 신뢰도 및 정비도 분석 프로세스 고찰)

  • Han, ChangHwan;Kim, KeunBae
    • Journal of the Korean Society of Systems Engineering
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    • v.12 no.1
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    • pp.105-112
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    • 2016
  • An aircraft must be designed to minimize system failure rate for obtaining the aircraft safety, because the aircraft system failure causes a fatal accident. The safety of the aircraft system can be predicted by analyzing availability, reliability, and maintainability of the system. In this study, the reliability and the maintainability of the hydraulic system are analysed except the availability, and therefore the reliability and the maintainability analysis process and the results are presented for a helicopter hydraulic system. For prediction of the system reliability, the failure rate model presented in MIL-HDBK-217F is used, and MTBF is calculated by using the Part Stress Analysis Prediction and quality/temperature/environmental factors described in NPRD-95 and MIL-HDBK-338B. The maintainability is predicted by FMECA(Failure Mode, Effect & Criticality Analysis) based on MIL-STD-1629A.

Neuro-Fuzzy Approaches to Ozone Prediction System (뉴로-퍼지 기법에 의한 오존농도 예측모델)

  • 김태헌;김성신;김인택;이종범;김신도;김용국
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.6
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    • pp.616-628
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    • 2000
  • In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

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Development of Back Analysis Program for Total Management Using Observational Method of Earth Retaining Structures under Ground Excavation (지반굴착 흙막이공의 정보화시공 종합관리를 위한 역해석 프로그램 개발)

  • 오정환;조철현;김성재;백영식
    • Proceedings of the Korean Geotechical Society Conference
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    • 2001.10c
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    • pp.103-122
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    • 2001
  • For prediction of ground movement per the excavation step, observational results of ground movement during the construction was very different with prediction during the analysis of design. step because of the uncertainty of the numerical analysis modelling, the soil parameter, and the condition of a construction field, etc. however accuratly numerical analysis method was applied. Therefore, the management system through the construction field measurement should be achieved for grasping the situation during the excavation. Until present, the measurement system restricted by ‘Absolute Value Management system’only analyzing the stability of present step was executed. So, it was difficult situation to expect the prediction of ground movement for the next excavation step. In this situation, it was developed that ‘The Management system TOMAS-EXCAV’ consisted of ‘Absolute value management system’ analyzing the stability of present step and ‘Prediction management system’ expecting the ground movement of next excavation step and analyzing the stability of next excavation step by‘Back Analysis’. TOMAS-EXCAV could be applied to all uncertainty of earth retaining structures analysis by connecting ‘Forward analysis program’ and ‘Back analysis program’ and optimizing the main design variables using SQP-MMFD optimization method through measurement results. The application of TOMAS-EXCAV was confirmed that verifed the three earth retaing construction field by back analysis.

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Displacement prediction in geotechnical engineering based on evolutionary neural network

  • Gao, Wei;He, T.Y.
    • Geomechanics and Engineering
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    • v.13 no.5
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    • pp.845-860
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    • 2017
  • It is very important to study displacement prediction in geotechnical engineering. Nowadays, the grey system method, time series analysis method and artificial neural network method are three main methods. Based on the brief introduction, the three methods are analyzed comprehensively. Their merits and demerits, applied ranges are revealed. To solve the shortcomings of the artificial neural network method, a new prediction method based on new evolutionary neural network is proposed. Finally, through two real engineering applications, the analysis of three main methods and the new evolutionary neural network method all have been verified. The results show that, the grey system method is a kind of exponential approximation to displacement sequence, and time series analysis is linear autoregression approximation, while artificial neural network is nonlinear autoregression approximation. Thus, the grey system method can suitably analyze the sequence, which has the exponential law, the time series method can suitably analyze the random sequence and the neural network method almostly can be applied in any sequences. Moreover, the prediction results of new evolutionary neural network method is the best, and its approximation sequence and the generalization prediction sequence are all coincided with the real displacement sequence well. Thus, the new evolutionary neural network method is an acceptable method to predict the measurement displacements of geotechnical engineering.

An Exploratory Study for Decreasing Error of Prediction Value of Recommended System on User Based

  • Lee, Hee-Choon
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.1
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    • pp.77-86
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    • 2006
  • This study is to investigate the error of prediction value with related variables from the recommended system and to examine the error of prediction value with related variables. To decrease the error on the collaborative recommended system on user based, this research explored the effects on the prediction related response pair between raters' demographic variables and Pearson's coefficient and sparsity. The result shows comparative analysis between existing error of prediction value and conditioned one.

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IoT Connectivity Application for Smart Building based on Analysis and Prediction System

  • COROTINSCHI, Ghenadie;FRANCU, Catalin;ZAGAN, Ionel;GAITAN, Vasile Gheorghita
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.103-108
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    • 2021
  • The emergence of new technologies and their implementation by different manufacturers of electronic devices are experiencing an ascending trend. Most of the time, these protocols are expected to reach a certain degree of maturity, and electronic equipment manufacturers use simplified communication standards and interfaces that have already reached maturity in terms of their development such as ModBUS, KNX or CAN. This paper proposes an IoT solution of the Smart Home type based on an Analysis and Prediction System. A data acquisition component was implemented and there was defined an algorithm for the analysis and prediction of actions based on the values collected from the data update component and the data logger records.

Marine Disasters Prediction System Model Using Marine Environment Monitoring (해양환경 모니터링을 이용한 해양재해 예측 시스템 모델)

  • Park, Sun;Lee, Seong Ro
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.3
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    • pp.263-270
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    • 2013
  • Recently, the prediction and analysis technology of marine environment are actively being studied since the ocean resources in the world is taken notice. The prediction of marine disaster by automatic collecting marine environment data and analyzing the collected data can contribute to minimized the damages with respect to marine pollution of oil spill and fisheries damage by red tide blooms and marine environment upsets. However the studies of the marine environment monitoring and analysis system are limited in South Korea. In this paper, we study the marine disasters prediction system model to analyze collection marine information of out sea and near sea. This paper proposes the models for the marine disasters prediction system as communication system model, a marine environment data monitoring system model, prediction and analyzing system model, and situations propagation system model. The red tide prediction model and summarizing and analyzing model is proposed for prediction and analyzing system model.

Analysis Model Evaluation based on IoT Data and Machine Learning Algorithm for Prediction of Acer Mono Sap Liquid Water

  • Lee, Han Sung;Jung, Se Hoon
    • Journal of Korea Multimedia Society
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    • v.23 no.10
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    • pp.1286-1295
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    • 2020
  • It has been increasingly difficult to predict the amounts of Acer mono sap to be collected due to droughts and cold waves caused by recent climate changes with few studies conducted on the prediction of its collection volume. This study thus set out to propose a Big Data prediction system based on meteorological information for the collection of Acer mono sap. The proposed system would analyze collected data and provide managers with a statistical chart of prediction values regarding climate factors to affect the amounts of Acer mono sap to be collected, thus enabling efficient work. It was designed based on Hadoop for data collection, treatment and analysis. The study also analyzed and proposed an optimal prediction model for climate conditions to influence the volume of Acer mono sap to be collected by applying a multiple regression analysis model based on Hadoop and Mahout.